Abstract
Cancer is a life-threatening disease and is the second leading cause of death worldwide. Although many drugs are available for the treatment of cancer, survival outcomes are very low. Hence, rapid development of newer anticancer agents is a prime focus of the medicinal chemistry community. Since the recent past, computational methods have been extensively employed for accelerating the drug discovery process. In view of this, in the present study we performed 2D-QSAR (Quantitative Structure-Activity Relationship) analysis of a series of compounds reported with potential anticancer activity against breast cancer cell line MCF7 using QSARINS software. The best four models exhibited a r2 value of 0.99. From the generated QSAR equations, a series of pyrimidine-coumarin-triazole conjugates were designed and their MCF7 cell inhibitory activities were predicted using the QSAR equations. Furthermore, molecular docking studies were carried out for the designed compounds using AutoDock Vina against dihydrofolate reductase (DHFR), colchicine and vinblastine binding sites of tubulin, the key enzyme targets in breast cancer. The most active compounds identified through these computational studies will be useful for synthesizing and testing them as prospective novel anti-breast cancer agents.
Highlights
Introduction iationsCancer is the second leading cause of death worldwide [1]
Mohit Sandhuja et al synthesized a series of uracil–coumarin conjugates and reported their anticancer activity [31]
The results clearly indicate that the best model obtained was not by chance and truly there is a relationship between structures of pyrimidine-coumarintriazole based trifunctional molecular hybrid analogs with corresponding MCF 7 cell line inhibitory activity
Summary
Cancer is the second leading cause of death worldwide [1]. Conventional cytotoxic chemotherapy has been a key component of advanced cancer treatment in the cancer therapeutic arsenal [2]. Only a minor improvement in survival rates has been achieved. Recent anticancer drug development is heavily reliant on drug targets, such as proteins, enzymes and receptors, and mechanism-based drug discovery would considerably accelerate the process. Various targets reported for anti-cancer activities include ribonucleotide reductase [6], estrogen receptors (ERs) [7,8], aromatase enzymes [9], type I and type II topoisomerases [10], microtubules [11] and dihydrofolate reductase, among others. Many targets are well-known and validated, still they offer various opportunities
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